Higher Circulating Testosterone Linked to Higher CAD Risk in Men: Mendelian Randomization and Survival Analyses
Bibliographic record
Abstract
CONTEXT: Testosterone supplementation is increasingly widespread and has well-established beneficial effects on sexual function and metabolic health. However, there remains uncertainty regarding associated cardiovascular risks. OBJECTIVE: Human genetics studies demonstrated that Mendelian randomization approaches recapitulate the beneficial effects of testosterone therapy; here we apply this to cardiovascular disease. DESIGN: We performed a Mendelian randomization study to assess the causal effect of higher circulating testosterone on coronary artery disease (CAD). We also tested the phenotypic association between measured circulating testosterone and CAD in the cohort of men aged 40 to 69. PATIENTS OR OTHER PARTICIPANTS: Testosterone genetic instrument data were derived from 425 097 European ancestry adults from the UK Biobank study and CAD from single nucleotide polymorphism-level summary statistics from 1 165 690 individuals in CARDIoGRAMplusC4D. MAIN OUTCOME MEASURE(S): CAD as defined in CARDIoGRAMplusC4D was the main outcome. In longitudinal analyses, CAD was defined according to medical records and self-report. RESULTS: We found that higher genetically predicted circulating testosterone conferred a higher risk of CAD in men [odds ratio (OR): 1.17, 95% confidence interval (CI) 1.07-1.27, P = 3.32 × 10-4]. There was no evidence of an effect in women (OR: 1.01, 95% CI 0.94-1.10, P = .73). The genetic association in men appeared to be mediated by higher blood pressure. In longitudinal observational analyses, a directionally opposite association was observed in men, likely arising due to confounding by type 2 diabetes and body mass index. CONCLUSION: These data suggest that increased testosterone may increase the risk of cardiovascular disease and that this safety concern should be a focus in future clinical trials for testosterone supplementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".